Results 21 to 30 of about 3,208 (258)

A Real-time Driving Drowsiness Detection Algorithm With Individual Differences Consideration

IEEE Access, 2019
The research work about driving drowsiness detection algorithm has great significance to improve traffic safety. Presently, there are many fruits and literature about driving drowsiness detection method.
Feng You, Xiaolong Li, Yunbo Gong, Haiwei Wang, Hongyi Li   +4 more
doaj   +1 more source

Image-based Driver Alert System for Prevention of Fatigue-related Accidents [PDF]

E3S Web of Conferences, 2023
The objective of this project is to design a driver unconsciousness detection system using image processing to detect drowsiness and unconsciousness in drivers, thereby preventing accidents resulting from driver fatigue.
Reddy G. Vijendar, Krishna P. Gopala, Sukanya L., Sri Harsha K., Vardhan N. Harsha, Arun V.   +5 more
doaj   +1 more source

Detecting Driver Drowsiness Based on Sensors: A Review

Sensors, 2012
In recent years, driver drowsiness has been one of the major causes of road accidents and can lead to severe physical injuries, deaths and significant economic losses.
Kenneth Sundaraj, Arun Sahayadhas, Murugappan Murugappan   +2 more
doaj   +1 more source

Automated Detection of Drowsiness using Machine Learning Approach [PDF]

E3S Web of Conferences, 2023
Nowadays, there is a steady rise in the number of traffic accidents. The primary causes of these accidents are impaired driving due to alcohol consumption and driver fatigue.
Sanjeeva Polepaka, Sriya Vallepu, Saniya Mahjabeen, Lohitha Matta, Ahmad Ishteyaaq, Swapna Rani K.   +5 more
doaj   +1 more source

Driver Drowsiness Estimation Based on Factorized Bilinear Feature Fusion and a Long-Short-Term Recurrent Convolutional Network

Information, 2020
The effective detection of driver drowsiness is an important measure to prevent traffic accidents. Most existing drowsiness detection methods only use a single facial feature to identify fatigue status, ignoring the complex correlation between fatigue ...
Shuang Chen, Zengcai Wang, Wenxin Chen
doaj   +1 more source

AUTOMOTIVE: A Case Study on AUTOmatic multiMOdal Drowsiness detecTIon for smart VEhicles

IEEE Access, 2021
As technology and artificial intelligence conquer a place under the spotlight in the automotive world, driver drowsiness monitoring systems have sparked much interest as a way to increase safety and avoid sleepiness-related accidents.
Telma Esteves, Joao Ribeiro Pinto, Pedro M. Ferreira, Pedro Amaro Costa, Lourenco Abrunhosa Rodrigues, Ines Antunes, Gabriel Lopes, Pedro Gamito, Arnaldo J. Abrantes, Pedro M. Jorge, Andre Lourenco, Ana F. Sequeira, Jaime S. Cardoso, Ana Rebelo   +13 more
doaj   +1 more source

A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness

Sensors, 2015
Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness.
Gang Li, Wan-Young Chung
doaj   +1 more source

Data fusion for driver drowsiness recognition: A multimodal perspective

Egyptian Informatics Journal
Drowsiness is characterized by decreased alertness and an increased inclination to fall asleep, typically from factors such as fatigue, sleep deprivation, or other related influences.
S. Priyanka, S. Shanthi, A. Saran Kumar, V. Praveen   +3 more
doaj   +1 more source

A Wearable Brain–Computer Interface for Mitigating Car Sickness via Attention Shifting

Advanced Science, EarlyView.
Car sickness poses a major challenge in vehicular travel, yet effective nonpharmacological solutions are scarce. We developed a wearable, closed‐loop mindfulness BCI that uses real‐time EEG‐based neurofeedback to shift attention away from motion‐induced discomfort. Validated in real‐car experiments involving >100$>100$ susceptible individuals, over 83%
Jiawei Zhu, Xiaoyu Bao, Qiyun Huang, Tao Wang, Li Huang, Haiyun Huang, Junbiao Zhu, Jun Qu, Kendi Li, Di Chen, Ya Jiang, Kailin Xu, Zijian Wang, Wei Wu, Yuanqing Li   +14 more
wiley   +1 more source

Effect of Laser Posterior Nasal Neurolysis for the Treatment of Chronic Rhinitis: A Randomized Controlled Trial

International Forum of Allergy &Rhinology, EarlyView.
ABSTRACT Background To determine the safety and efficacy of laser ablation of the posterior nasal nerve (PNN) for the treatment of chronic rhinitis. Methods This study was a single‐center, prospective, single‐blinded, randomized sham‐controlled trial. Patients with a 24‐h reflective Total Nasal Symptom Score (rTNSS) ≧ 5, rhinorrhea ≧ 2, and congestion ≧
Jyun‐Yi Liao, En‐Ying Wang, Ying‐Shuo Hsu, Ming‐Shao Tsai, Cheng‐Jung Wu, Chia‐Hao Chang, Yi‐Li Hwang, Han‐Lo Teng, Jun‐Wei Hsieh, Chien‐Yu Huang   +9 more
wiley   +1 more source